Articles | Volume 22, issue 4
https://doi.org/10.5194/nhess-22-1469-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-22-1469-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Machine-learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains
Andrea Magnini
CORRESPONDING AUTHOR
Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, Bologna, Italy
Michele Lombardi
Department of Computer Science and Engineering (DISI), University of Bologna, Bologna, Italy
Simone Persiano
Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, Bologna, Italy
Antonio Tirri
Leithà, Unipol Group, Milan and Bologna, Italy
Francesco Lo Conti
Leithà, Unipol Group, Milan and Bologna, Italy
Attilio Castellarin
Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, Bologna, Italy
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Simone Persiano, Alessio Pugliese, Alberto Aloe, Jon Olav Skøien, Attilio Castellarin, and Alberto Pistocchi
Earth Syst. Sci. Data, 14, 4435–4443, https://doi.org/10.5194/essd-14-4435-2022, https://doi.org/10.5194/essd-14-4435-2022, 2022
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For about 24000 river basins across Europe, this study provides a continuous representation of the streamflow regime in terms of empirical flow–duration curves (FDCs), which are key signatures of the hydrological behaviour of a catchment and are widely used for supporting decisions on water resource management as well as for assessing hydrologic change. FDCs at ungauged sites are estimated by means of a geostatistical procedure starting from data observed at about 3000 sites across Europe.
Mattia Amadio, Anna Rita Scorzini, Francesca Carisi, Arthur H. Essenfelder, Alessio Domeneghetti, Jaroslav Mysiak, and Attilio Castellarin
Nat. Hazards Earth Syst. Sci., 19, 661–678, https://doi.org/10.5194/nhess-19-661-2019, https://doi.org/10.5194/nhess-19-661-2019, 2019
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Flood risk management relies on assessments performed using flood loss models of different complexities. We compared the performances of expert-based and empirical damage models on three major flood events in northern Italy. Our findings suggest that multivariate models have better potential to provide reliable damage estimates if extensive ancillary characterisation data are available. Expert-based approaches are better suited for transferability compared to empirically based approaches.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Proc. IAHS, 380, 3–8, https://doi.org/10.5194/piahs-380-3-2018, https://doi.org/10.5194/piahs-380-3-2018, 2018
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 5735–5739, https://doi.org/10.5194/hess-22-5735-2018, https://doi.org/10.5194/hess-22-5735-2018, 2018
Alessio Pugliese, Simone Persiano, Stefano Bagli, Paolo Mazzoli, Juraj Parajka, Berit Arheimer, René Capell, Alberto Montanari, Günter Blöschl, and Attilio Castellarin
Hydrol. Earth Syst. Sci., 22, 4633–4648, https://doi.org/10.5194/hess-22-4633-2018, https://doi.org/10.5194/hess-22-4633-2018, 2018
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This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.
Francesca Carisi, Kai Schröter, Alessio Domeneghetti, Heidi Kreibich, and Attilio Castellarin
Nat. Hazards Earth Syst. Sci., 18, 2057–2079, https://doi.org/10.5194/nhess-18-2057-2018, https://doi.org/10.5194/nhess-18-2057-2018, 2018
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By analyzing a comprehensive loss dataset of affected private households after a recent river flood event in northern Italy, we tackle the problem of flood damage estimation in Emilia-Romagna (Italy). We develop empirical uni- and multivariable loss models for the residential sector. Outcomes highlight that the latter seem to outperform the former and, in addition, results show a higher accuracy of univariable models based on local data compared to literature ones derived for different contexts.
Francesca Carisi, Alessio Domeneghetti, and Attilio Castellarin
Proc. IAHS, 373, 161–166, https://doi.org/10.5194/piahs-373-161-2016, https://doi.org/10.5194/piahs-373-161-2016, 2016
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Can differential land-subsidence significantly alter river flooding dynamics, and thus flood risk in flood prone areas? In the area around Ravenna, in Italy, that experimented a cumulative drop of more than 1.5 m after World War II due to groundwater pumping and gas production platforms, we compared the actual effects on flood-hazard dynamics of differential land-subsidence relative to those associated with other man-made topographic alterations, which proved to be much more significant.
Simone Persiano, Attilio Castellarin, Jose Luis Salinas, Alessio Domeneghetti, and Armando Brath
Proc. IAHS, 373, 95–100, https://doi.org/10.5194/piahs-373-95-2016, https://doi.org/10.5194/piahs-373-95-2016, 2016
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The growing concern about the possible effects of climate change on flood frequency regime is leading Authorities to review reference procedures for design flood estimation. Our study focuses on Triveneto (Italy) and proposes an update of the existing reference procedure by properly considering climate and scale controls on flood frequency. Moreover, the study highlights the remarkable influence of a single extreme-floods year on analyses for detecting possible changes in flood frequency regime.
F. Carisi, A. Domeneghetti, and A. Castellarin
Proc. IAHS, 370, 209–215, https://doi.org/10.5194/piahs-370-209-2015, https://doi.org/10.5194/piahs-370-209-2015, 2015
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Our study proposes simplified graphical tools (Hypsometric Vulnerability Curves) for assessing the recent dynamics of the flood vulnerability and risk over a large floodable area along the River Po, Northern Italy, and for defining sustainable flood-risk mitigation strategies. We assess the accuracy of the proposed methodology, based on inundation scenarios simulated with a quasi-2D model, by means of a comparison with a traditional approach relying on the simulations of a to a fully-2D model.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
S. Ceola, B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione, and T. Wagener
Hydrol. Earth Syst. Sci., 19, 2101–2117, https://doi.org/10.5194/hess-19-2101-2015, https://doi.org/10.5194/hess-19-2101-2015, 2015
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We present the outcomes of a collaborative hydrological experiment undertaken by five different international research groups in a virtual laboratory. Moving from the definition of accurate protocols, a rainfall-runoff model was independently applied by the research groups, which then engaged in a comparative discussion. The results revealed that sharing protocols and running the experiment within a controlled environment is fundamental for ensuring experiment repeatability and reproducibility.
J. L. Salinas, A. Castellarin, A. Viglione, S. Kohnová, and T. R. Kjeldsen
Hydrol. Earth Syst. Sci., 18, 4381–4389, https://doi.org/10.5194/hess-18-4381-2014, https://doi.org/10.5194/hess-18-4381-2014, 2014
A. Pugliese, A. Castellarin, and A. Brath
Hydrol. Earth Syst. Sci., 18, 3801–3816, https://doi.org/10.5194/hess-18-3801-2014, https://doi.org/10.5194/hess-18-3801-2014, 2014
A. Domeneghetti, S. Vorogushyn, A. Castellarin, B. Merz, and A. Brath
Hydrol. Earth Syst. Sci., 17, 3127–3140, https://doi.org/10.5194/hess-17-3127-2013, https://doi.org/10.5194/hess-17-3127-2013, 2013
S. A. Archfield, A. Pugliese, A. Castellarin, J. O. Skøien, and J. E. Kiang
Hydrol. Earth Syst. Sci., 17, 1575–1588, https://doi.org/10.5194/hess-17-1575-2013, https://doi.org/10.5194/hess-17-1575-2013, 2013
E. Baratti, A. Montanari, A. Castellarin, J. L. Salinas, A. Viglione, and A. Bezzi
Hydrol. Earth Syst. Sci., 16, 4651–4660, https://doi.org/10.5194/hess-16-4651-2012, https://doi.org/10.5194/hess-16-4651-2012, 2012
Related subject area
Hydrological Hazards
Brief communication: A first hydrological investigation of extreme August 2023 floods in Slovenia, Europe
Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin
Review article: Towards improved drought prediction in the Mediterranean region – modeling approaches and future directions
Assessing typhoon-induced compound flood drivers: a case study in Ho Chi Minh City, Vietnam
Assessing the ability of a new seamless short-range ensemble rainfall product to anticipate flash floods in the French Mediterranean area
Sentinel-1-based analysis of the severe flood over Pakistan 2022
Current and Future Rainfall-Driven Flood Risk From Hurricanes in Puerto Rico Under 1.5 °C and 2 °C Climate Change
Sensitivity analysis of erosion on the landward slope of an earthen flood defense located in southern France submitted to wave overtopping
Better prepared but less resilient: the paradoxical impact of frequent flood experience on adaptive behavior and resilience
Assessing the spatial spread–skill of ensemble flood maps with remote-sensing observations
An integrated modeling approach to evaluate the impacts of nature-based solutions of flood mitigation across a small watershed in the southeast United States
Indicator-to-impact links to help improve agricultural drought preparedness in Thailand
The potential of open-access data for flood estimations: uncovering inundation hotspots in Ho Chi Minh City, Vietnam, through a normalized flood severity index
Analyzing the informative value of alternative hazard indicators for monitoring drought hazard for human water supply and river ecosystems at the global scale
Using integrated hydrological-hydraulic modelling and global data sources to analyse the February 2023 floods in the Umbeluzi catchment (Mozambique)
Assessing the next generation of Global Flood Models in the Central Highlands of Vietnam
A methodological framework for the evaluation of short-range flash-flood hydrometeorological forecasts at the event scale
Impact-based flood forecasting in the Greater Horn of Africa
Hydrological drought forecasting under a changing environment in the Luanhe River basin
A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 2: Historical context and relation to climate change
Brief communication: The potential use of low-cost acoustic sensors to detect rainfall for short-term urban flood warnings
Brief communication: On the extremeness of the July 2021 precipitation event in western Germany
A climate-conditioned catastrophe risk model for UK flooding
A globally applicable framework for compound flood hazard modeling
Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany
Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90
Brief communication: Inclusiveness in designing an early warning system for flood resilience
Evolution of multivariate drought hazard, vulnerability and risk in India under climate change
CRHyME (Climatic Rainfall Hydrogeological Model Experiment): a new model for geo-hydrological hazard assessment at the basin scale
A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 1: Event description and analysis
Bare-earth DEM generation from ArcticDEM and its use in flood simulation
Comparison of estimated flood exposure and consequences generated by different event-based inland flood inundation maps
How uncertain are precipitation and peak flow estimates for the July 2021 flooding event?
Estimating the likelihood of roadway pluvial flood based on crowdsourced traffic data and depression-based DEM analysis
A multi-strategy-mode waterlogging-prediction framework for urban flood depth
Multiscale flood risk assessment under climate change: the case of the Miño River in the city of Ourense, Spain
Interactions between precipitation, evapotranspiration and soil-moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data
How to mitigate flood events similar to the 1979 catastrophic floods in lower Tagus
Rare flood scenarios for a rapidly growing high-mountain city: Pokhara, Nepal
Brief communication: Impact forecasting could substantially improve the emergency management of deadly floods: case study July 2021 floods in Germany
Brief communication: Western Europe flood in 2021 – mapping agriculture flood exposure from synthetic aperture radar (SAR)
Comprehensive space–time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin
A new index to quantify the extremeness of precipitation across scales
Effectiveness of Sentinel-1 and Sentinel-2 for flood detection assessment in Europe
Assessing flood hazard changes using climate model forcing
Characterizing multivariate coastal flooding events in a semi-arid region: the implications of copula choice, sampling, and infrastructure
Different drought types and the spatial variability in their hazard, impact, and propagation characteristics
More than heavy rain turning into fast-flowing water – a landscape perspective on the 2021 Eifel floods
Integrated drought risk assessment to support adaptive policymaking in the Netherlands
INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium)
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Ana Paez-Trujilo, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, and Dimitri Solomatine
Nat. Hazards Earth Syst. Sci., 23, 3863–3883, https://doi.org/10.5194/nhess-23-3863-2023, https://doi.org/10.5194/nhess-23-3863-2023, 2023
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This study uses a machine learning technique, the multivariate regression tree approach, to assess the hydroclimatic characteristics that govern agricultural and hydrological drought severity. The results show that the employed technique successfully identified the primary drivers of droughts and their critical thresholds. In addition, it provides relevant information to identify the areas most vulnerable to droughts and design strategies and interventions for drought management.
Bouchra Zellou, Nabil El Moçayd, and El Houcine Bergou
Nat. Hazards Earth Syst. Sci., 23, 3543–3583, https://doi.org/10.5194/nhess-23-3543-2023, https://doi.org/10.5194/nhess-23-3543-2023, 2023
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In this study, we underscore the critical importance of strengthening drought prediction capabilities in the Mediterranean region. We present an in-depth evaluation of current drought forecasting approaches, encompassing statistical, dynamical, and hybrid statistical–dynamical models, and highlight unexplored research opportunities. Additionally, we suggest viable directions to enhance drought prediction and early warning systems within the area.
Francisco Rodrigues do Amaral, Nicolas Gratiot, Thierry Pellarin, and Tran Anh Tu
Nat. Hazards Earth Syst. Sci., 23, 3379–3405, https://doi.org/10.5194/nhess-23-3379-2023, https://doi.org/10.5194/nhess-23-3379-2023, 2023
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We propose an in-depth analysis of typhoon-induced compound flood drivers in the megacity of Ho Chi Minh, Vietnam. We use in situ and satellite measurements throughout the event to form a holistic overview of its impact. No evidence of storm surge was found, and peak precipitation presents a 16 h time lag to peak river discharge, which evacuates only 1.5 % of available water. The astronomical tide controls the river level even during the extreme event, and it is the main urban flood driver.
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
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This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
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In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Leanne Archer, Jeffrey Neal, Paul Bates, Emily Vosper, Dereka Carroll, Jeison Sosa, and Daniel Mitchell
EGUsphere, https://doi.org/10.5194/egusphere-2023-1574, https://doi.org/10.5194/egusphere-2023-1574, 2023
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We model hurricane rainfall-driven flooding to assess how the number of people exposed to flooding changes in Puerto Rico under the 1.5 °C and 2 °C Paris Agreement Goals. Our analysis suggests 8–10 % of the population is currently exposed to flooding on average every 5 years, increasing by 2–15 % and 1–20 % at 1.5 °C and 2 °C. This has implications for adaptation to more extreme flooding in Puerto Rico and demonstrates that 1.5 °C climate change carries a significant increase in risk.
Clément Houdard, Adrien Poupardin, Philippe Sergent, Abdelkrim Bennabi, and Jena Jeong
Nat. Hazards Earth Syst. Sci., 23, 3111–3124, https://doi.org/10.5194/nhess-23-3111-2023, https://doi.org/10.5194/nhess-23-3111-2023, 2023
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We developed a system able to to predict, knowing the appropriate characteristics of the flood defense structure and sea state, the return periods of potentially dangerous events as well as a ranking of parameters by order of uncertainty.
The model is a combination of statistical and empirical methods that have been applied to a Mediterranean earthen dike. This shows that the most important characteristics of the dyke are its geometrical features, such as its height and slope angles.
Lisa Köhler, Torsten Masson, Sabrina Köhler, and Christian Kuhlicke
Nat. Hazards Earth Syst. Sci., 23, 2787–2806, https://doi.org/10.5194/nhess-23-2787-2023, https://doi.org/10.5194/nhess-23-2787-2023, 2023
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We analyzed the impact of flood experience on adaptive behavior and self-reported resilience. The outcomes draw a paradoxical picture: the most experienced people are the most adapted but the least resilient. We find evidence for non-linear relationships between the number of floods experienced and resilience. We contribute to existing knowledge by focusing specifically on the number of floods experienced and extending the rare scientific literature on the influence of experience on resilience.
Helen Hooker, Sarah L. Dance, David C. Mason, John Bevington, and Kay Shelton
Nat. Hazards Earth Syst. Sci., 23, 2769–2785, https://doi.org/10.5194/nhess-23-2769-2023, https://doi.org/10.5194/nhess-23-2769-2023, 2023
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Ensemble forecasts of flood inundation produce maps indicating the probability of flooding. A new approach is presented to evaluate the spatial performance of an ensemble flood map forecast by comparison against remotely observed flooding extents. This is important for understanding forecast uncertainties and improving flood forecasting systems.
Betina I. Guido, Ioana Popescu, Vidya Samadi, and Biswa Bhattacharya
Nat. Hazards Earth Syst. Sci., 23, 2663–2681, https://doi.org/10.5194/nhess-23-2663-2023, https://doi.org/10.5194/nhess-23-2663-2023, 2023
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We used an integrated model to evaluate the impacts of nature-based solutions (NBSs) on flood mitigation across the Little Pee Dee and Lumber River watershed, the Carolinas, US. This area is strongly affected by climatic disasters, which are expected to increase due to climate change and urbanization, so exploring an NBS approach is crucial for adapting to future alterations. Our research found that NBSs can have visible effects on the reduction in hurricane-driven flooding.
Maliko Tanguy, Michael Eastman, Eugene Magee, Lucy J. Barker, Thomas Chitson, Chaiwat Ekkawatpanit, Daniel Goodwin, Jamie Hannaford, Ian Holman, Liwa Pardthaisong, Simon Parry, Dolores Rey Vicario, and Supattra Visessri
Nat. Hazards Earth Syst. Sci., 23, 2419–2441, https://doi.org/10.5194/nhess-23-2419-2023, https://doi.org/10.5194/nhess-23-2419-2023, 2023
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Droughts in Thailand are becoming more severe due to climate change. Understanding the link between drought impacts on the ground and drought indicators used in drought monitoring systems can help increase a country's preparedness and resilience to drought. With a focus on agricultural droughts, we derive crop- and region-specific indicator-to-impact links that can form the basis of targeted mitigation actions and an improved drought monitoring and early warning system in Thailand.
Leon Scheiber, Mazen Hoballah Jalloul, Christian Jordan, Jan Visscher, Hong Quan Nguyen, and Torsten Schlurmann
Nat. Hazards Earth Syst. Sci., 23, 2313–2332, https://doi.org/10.5194/nhess-23-2313-2023, https://doi.org/10.5194/nhess-23-2313-2023, 2023
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Numerical models are increasingly important for assessing urban flooding, yet reliable input data are oftentimes hard to obtain. Taking Ho Chi Minh City as an example, this paper explores the usability and reliability of open-access data to produce preliminary risk maps that provide first insights into potential flooding hotspots. As a key novelty, a normalized flood severity index is presented which combines flood depth and duration to enhance the interpretation of hydro-numerical results.
Claudia Herbert and Petra Döll
Nat. Hazards Earth Syst. Sci., 23, 2111–2131, https://doi.org/10.5194/nhess-23-2111-2023, https://doi.org/10.5194/nhess-23-2111-2023, 2023
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This paper presents a new method for selecting streamflow drought hazard indicators for monitoring drought hazard for human water supply and river ecosystems in large-scale drought early warning systems. Indicators are classified by their inherent assumptions about the habituation of people and ecosystems to the streamflow regime and their level of drought characterization, namely drought magnitude (water deficit at a certain point in time) and severity (cumulated magnitude since drought onset).
Luis Cea, Manuel Álvarez, and Jerónimo Puertas
EGUsphere, https://doi.org/10.5194/egusphere-2023-1003, https://doi.org/10.5194/egusphere-2023-1003, 2023
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Mozambique is highly exposed to the impact of floods. To reduce flood damage, it is necessary to develop mitigation measures. Hydrological software is a very useful tool for that purpose, since it allows a precise quantification of flood hazard under different scenarios. We present a methodology to quantify flood hazard in data scarce regions, using freely available data and software, and we show its potential by analysing the flood event that took place in the Umbeluzi basin in February 2023.
Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Khanh Pham Nam
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-93, https://doi.org/10.5194/nhess-2023-93, 2023
Revised manuscript accepted for NHESS
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A global flood model built using a new terrain dataset and evaluated in the central highlands of Vietnam.
Maryse Charpentier-Noyer, Daniela Peredo, Axelle Fleury, Hugo Marchal, François Bouttier, Eric Gaume, Pierre Nicolle, Olivier Payrastre, and Maria-Helena Ramos
Nat. Hazards Earth Syst. Sci., 23, 2001–2029, https://doi.org/10.5194/nhess-23-2001-2023, https://doi.org/10.5194/nhess-23-2001-2023, 2023
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This paper proposes a methodological framework designed for event-based evaluation in the context of an intense flash-flood event. The evaluation adopts the point of view of end users, with a focus on the anticipation of exceedances of discharge thresholds. With a study of rainfall forecasts, a discharge evaluation and a detailed look at the forecast hydrographs, the evaluation framework should help in drawing robust conclusions about the usefulness of new rainfall ensemble forecasts.
Lorenzo Alfieri, Andrea Libertino, Lorenzo Campo, Francesco Dottori, Simone Gabellani, Tatiana Ghizzoni, Alessandro Masoero, Lauro Rossi, Roberto Rudari, Nicola Testa, Eva Trasforini, Ahmed Amdihun, Jully Ouma, Luca Rossi, Yves Tramblay, Huan Wu, and Marco Massabò
EGUsphere, https://doi.org/10.5194/egusphere-2023-804, https://doi.org/10.5194/egusphere-2023-804, 2023
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This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the Greater Horn of Africa. It is based on hydrological simulations, inundation mapping, and estimation of population and assets exposed to upcoming river floods. The system supports duty officers in African institutions in the daily monitoring of hydro-meteorological disasters. A first evaluation shows the system performance for the catastrophic floods in the Nile River Basin in Summer 2020.
Min Li, Mingfeng Zhang, Runxiang Cao, Yidi Sun, and Xiyuan Deng
Nat. Hazards Earth Syst. Sci., 23, 1453–1464, https://doi.org/10.5194/nhess-23-1453-2023, https://doi.org/10.5194/nhess-23-1453-2023, 2023
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It is an important disaster reduction strategy to forecast hydrological drought. In order to analyse the impact of human activities on hydrological drought, we constructed the human activity factor based on the method of restoration. With the increase of human index (HI) value, hydrological droughts tend to transition to more severe droughts. The conditional distribution model involving of human activity factor can further improve the forecasting accuracy of drought in the Luanhe River basin.
Patrick Ludwig, Florian Ehmele, Mário J. Franca, Susanna Mohr, Alberto Caldas-Alvarez, James E. Daniell, Uwe Ehret, Hendrik Feldmann, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Michael Kunz, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 1287–1311, https://doi.org/10.5194/nhess-23-1287-2023, https://doi.org/10.5194/nhess-23-1287-2023, 2023
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Heavy precipitation in July 2021 led to widespread floods in western Germany and neighboring countries. The event was among the five heaviest precipitation events of the past 70 years in Germany, and the river discharges exceeded by far the statistical 100-year return values. Simulations of the event under future climate conditions revealed a strong and non-linear effect on flood peaks: for +2 K global warming, an 18 % increase in rainfall led to a 39 % increase of the flood peak in the Ahr river.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
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Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Katharina Lengfeld, Paul Voit, Frank Kaspar, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 1227–1232, https://doi.org/10.5194/nhess-23-1227-2023, https://doi.org/10.5194/nhess-23-1227-2023, 2023
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Estimating the severity of a rainfall event based on the damage caused is easy but highly depends on the affected region. A less biased measure for the extremeness of an event is its rarity combined with its spatial extent. In this brief communication, we investigate the sensitivity of such measures to the underlying dataset and highlight the importance of considering multiple spatial and temporal scales using the devastating rainfall event in July 2021 in central Europe as an example.
Paul D. Bates, James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith
Nat. Hazards Earth Syst. Sci., 23, 891–908, https://doi.org/10.5194/nhess-23-891-2023, https://doi.org/10.5194/nhess-23-891-2023, 2023
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We present and validate a model that simulates current and future flood risk for the UK at high resolution (~ 20–25 m). We show that UK flood losses were ~ 6 % greater in the climate of 2020 compared to recent historical values. The UK can keep any future increase to ~ 8 % if all countries implement their COP26 pledges and net-zero ambitions in full. However, if only the COP26 pledges are fulfilled, then UK flood losses increase by ~ 23 %; and potentially by ~ 37 % in a worst-case scenario.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
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In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Omar Seleem, Georgy Ayzel, Axel Bronstert, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 809–822, https://doi.org/10.5194/nhess-23-809-2023, https://doi.org/10.5194/nhess-23-809-2023, 2023
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Data-driven models are becoming more of a surrogate that overcomes the limitations of the computationally expensive 2D hydrodynamic models to map urban flood hazards. However, the model's ability to generalize outside the training domain is still a major challenge. We evaluate the performance of random forest and convolutional neural networks to predict urban floodwater depth and investigate their transferability outside the training domain.
Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-9, https://doi.org/10.5194/nhess-2023-9, 2023
Revised manuscript under review for NHESS
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The study presents a new version of a framework which allow to model water balance components at any site for a local scale. In comparison to the first version, the second one incorporates new datasets used to setup and force the model. In particular, we want to highlight the ability of the framework to provide seasonal forecasts. This gives the potential stakeholders (farmers, foresters, policymakers etc.) possibility to forecast e.g. soil moisture drought and thus apply necessary measures.
Tahmina Yasmin, Kieran Khamis, Anthony Ross, Subir Sen, Anita Sharma, Debashish Sen, Sumit Sen, Wouter Buytaert, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 23, 667–674, https://doi.org/10.5194/nhess-23-667-2023, https://doi.org/10.5194/nhess-23-667-2023, 2023
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Floods continue to be a wicked problem that require developing early warning systems with plausible assumptions of risk behaviour, with more targeted conversations with the community at risk. Through this paper we advocate the use of a SMART approach to encourage bottom-up initiatives to develop inclusive and purposeful early warning systems that benefit the community at risk by engaging them at every step of the way along with including other stakeholders at multiple scales of operations.
Venkataswamy Sahana and Arpita Mondal
Nat. Hazards Earth Syst. Sci., 23, 623–641, https://doi.org/10.5194/nhess-23-623-2023, https://doi.org/10.5194/nhess-23-623-2023, 2023
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In an agriculture-dependent, densely populated country such as India, drought risk projection is important to assess future water security. This study presents the first comprehensive drought risk assessment over India, integrating hazard and vulnerability information. Future drought risk is found to be more significantly driven by increased vulnerability resulting from societal developments rather than climate-induced changes in hazard. These findings can inform planning for drought resilience.
Andrea Abbate, Leonardo Mancusi, Antonella Frigerio, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-15, https://doi.org/10.5194/nhess-2023-15, 2023
Revised manuscript accepted for NHESS
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CRHyME (Climatic Rainfall Hydrogeological Model Experiment) is a new spatially distributed rainfall-runoff model. The main novelties are: the ability to integrate with climatic scenario outputs and the reproduction of geo-hydrological hazards strongly related to rainfalls such as shallow landslide, debris flow and watershed erosion. CRHyME has been written in PYTHON and works at a high spatial and temporal resolution to simulate geo-hydrological hazards triggered by extreme rainfall events.
Susanna Mohr, Uwe Ehret, Michael Kunz, Patrick Ludwig, Alberto Caldas-Alvarez, James E. Daniell, Florian Ehmele, Hendrik Feldmann, Mário J. Franca, Christian Gattke, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Marc Scheibel, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 525–551, https://doi.org/10.5194/nhess-23-525-2023, https://doi.org/10.5194/nhess-23-525-2023, 2023
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The flood event in July 2021 was one of the most severe disasters in Europe in the last half century. The objective of this two-part study is a multi-disciplinary assessment that examines the complex process interactions in different compartments, from meteorology to hydrological conditions to hydro-morphological processes to impacts on assets and environment. In addition, we address the question of what measures are possible to generate added value to early response management.
Yinxue Liu, Paul D. Bates, and Jeffery C. Neal
Nat. Hazards Earth Syst. Sci., 23, 375–391, https://doi.org/10.5194/nhess-23-375-2023, https://doi.org/10.5194/nhess-23-375-2023, 2023
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In this paper, we test two approaches for removing buildings and other above-ground objects from a state-of-the-art satellite photogrammetry topography product, ArcticDEM. Our best technique gives a 70 % reduction in vertical error, with an average difference of 1.02 m from a benchmark lidar for the city of Helsinki, Finland. When used in a simulation of rainfall-driven flooding, the bare-earth version of ArcticDEM yields a significant improvement in predicted inundation extent and water depth.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mohammad S. Islam, Oliver E. J. Wing, William P. Lehman, Chase O. Hamilton, Mark D. Wahl, and T. Christopher Massey
Nat. Hazards Earth Syst. Sci., 23, 261–277, https://doi.org/10.5194/nhess-23-261-2023, https://doi.org/10.5194/nhess-23-261-2023, 2023
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Emergency managers use event-based flood inundation maps (FIMs) to plan and coordinate flood emergency response. We perform a case study test of three different FIM frameworks to see if FIM differences lead to substantial differences in the location and magnitude of flood exposure and consequences. We find that the FIMs are very different spatially and that the spatial differences do produce differences in the location and magnitude of exposure and consequences.
Mohamed Saadi, Carina Furusho-Percot, Alexandre Belleflamme, Ju-Yu Chen, Silke Trömel, and Stefan Kollet
Nat. Hazards Earth Syst. Sci., 23, 159–177, https://doi.org/10.5194/nhess-23-159-2023, https://doi.org/10.5194/nhess-23-159-2023, 2023
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On 14 July 2021, heavy rainfall fell over central Europe, causing considerable damage and human fatalities. We analyzed how accurate our estimates of rainfall and peak flow were for these flooding events in western Germany. We found that the rainfall estimates from radar measurements were improved by including polarimetric variables and their vertical gradients. Peak flow estimates were highly uncertain due to uncertainties in hydrological model parameters and rainfall measurements.
Arefeh Safaei-Moghadam, David Tarboton, and Barbara Minsker
Nat. Hazards Earth Syst. Sci., 23, 1–19, https://doi.org/10.5194/nhess-23-1-2023, https://doi.org/10.5194/nhess-23-1-2023, 2023
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Climate change, urbanization, and aging infrastructure contribute to flooding on roadways. This study evaluates the potential for flood reports collected from Waze – a community-based navigation app – to predict these events. Waze reports correlate primarily with low-lying depressions on roads. Therefore, we developed two data-driven models to determine whether roadways will flood. Analysis showed that in the city of Dallas, drainage area and imperviousness are the most significant contributors.
Zongjia Zhang, Jun Liang, Yujue Zhou, Zhejun Huang, Jie Jiang, Junguo Liu, and Lili Yang
Nat. Hazards Earth Syst. Sci., 22, 4139–4165, https://doi.org/10.5194/nhess-22-4139-2022, https://doi.org/10.5194/nhess-22-4139-2022, 2022
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An innovative multi-strategy-mode waterlogging-prediction framework for predicting waterlogging depth is proposed in the paper. The framework selects eight regression algorithms for comparison and tests the prediction accuracy and robustness of the model under different prediction strategies. Ultimately, the accuracy of predicting water depth after 30 min can exceed 86.1 %. This can aid decision-making in terms of issuing early warning information and determining emergency responses in advance.
Diego Fernández-Nóvoa, Orlando García-Feal, José González-Cao, Maite deCastro, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci., 22, 3957–3972, https://doi.org/10.5194/nhess-22-3957-2022, https://doi.org/10.5194/nhess-22-3957-2022, 2022
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A multiscale analysis, where the historical and future precipitation data from the CORDEX project were used as input in a hydrological model (HEC-HMS) that, in turn, feeds a 2D hydraulic model (Iber+), was applied to the case of the Miño-Sil basin (NW Spain), specifically to Ourense city, in order to analyze future changes in flood hazard. Detailed flood maps indicate an increase in the frequency and intensity of future floods, implying an increase in flood hazard in important areas of the city.
Jaime Gaona, Pere Quintana-Seguí, María José Escorihuela, Aaron Boone, and María Carmen Llasat
Nat. Hazards Earth Syst. Sci., 22, 3461–3485, https://doi.org/10.5194/nhess-22-3461-2022, https://doi.org/10.5194/nhess-22-3461-2022, 2022
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Droughts represent a particularly complex natural hazard and require explorations of their multiple causes. Part of the complexity has roots in the interaction between the continuous changes in and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.
Diego Fernández-Nóvoa, Alexandre M. Ramos, José González-Cao, Orlando García-Feal, Cristina Catita, Moncho Gómez-Gesteira, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-243, https://doi.org/10.5194/nhess-2022-243, 2022
Revised manuscript accepted for NHESS
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The present study focuses on an in depth analysis of floods in the lower section of the Tagus river from a hydrodynamic perspective by means of Iber+ numerical model and on the development of dam operating strategies to mitigate the flood episodes using the outstating floods of February 1979 as benchmark. Obtained results corroborate the model capability to evaluate floods in the study area and confirm the effectiveness of the proposed strategies to reduce flood impact in lower Tagus valley.
Melanie Fischer, Jana Brettin, Sigrid Roessner, Ariane Walz, Monique Fort, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 22, 3105–3123, https://doi.org/10.5194/nhess-22-3105-2022, https://doi.org/10.5194/nhess-22-3105-2022, 2022
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Nepal’s second-largest city has been rapidly growing since the 1970s, although its valley has been affected by rare, catastrophic floods in recent and historic times. We analyse potential impacts of such floods on urban areas and infrastructure by modelling 10 physically plausible flood scenarios along Pokhara’s main river. We find that hydraulic effects would largely affect a number of squatter settlements, which have expanded rapidly towards the river by a factor of up to 20 since 2008.
Heiko Apel, Sergiy Vorogushyn, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 22, 3005–3014, https://doi.org/10.5194/nhess-22-3005-2022, https://doi.org/10.5194/nhess-22-3005-2022, 2022
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The paper presents a fast 2D hydraulic simulation model for flood propagation that enables operational forecasts of spatially distributed inundation depths, flood extent, flow velocities, and other flood impacts. The detailed spatial forecast of floods and flood impacts is a large step forward from the currently operational forecasts of discharges at selected gauges, thus enabling a more targeted flood management and early warning.
Kang He, Qing Yang, Xinyi Shen, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 22, 2921–2927, https://doi.org/10.5194/nhess-22-2921-2022, https://doi.org/10.5194/nhess-22-2921-2022, 2022
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This study depicts the flood-affected areas in western Europe in July 2021 and particularly the agriculture land that was under flood inundation. The results indicate that the total inundated area over western Europe is about 1920 km2, of which 1320 km2 is in France. Around 64 % of the inundated area is agricultural land. We expect that the agricultural productivity in western Europe will have been severely impacted.
Daniel Viviroli, Anna E. Sikorska-Senoner, Guillaume Evin, Maria Staudinger, Martina Kauzlaric, Jérémy Chardon, Anne-Catherine Favre, Benoit Hingray, Gilles Nicolet, Damien Raynaud, Jan Seibert, Rolf Weingartner, and Calvin Whealton
Nat. Hazards Earth Syst. Sci., 22, 2891–2920, https://doi.org/10.5194/nhess-22-2891-2022, https://doi.org/10.5194/nhess-22-2891-2022, 2022
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Estimating the magnitude of rare to very rare floods is a challenging task due to a lack of sufficiently long observations. The challenge is even greater in large river basins, where precipitation patterns and amounts differ considerably between individual events and floods from different parts of the basin coincide. We show that a hydrometeorological model chain can provide plausible estimates in this setting and can thus inform flood risk and safety assessments for critical infrastructure.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 22, 2791–2805, https://doi.org/10.5194/nhess-22-2791-2022, https://doi.org/10.5194/nhess-22-2791-2022, 2022
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To better understand how the frequency and intensity of heavy precipitation events (HPEs) will change with changing climate and to adapt disaster risk management accordingly, we have to quantify the extremeness of HPEs in a reliable way. We introduce the xWEI (cross-scale WEI) and show that this index can reveal important characteristics of HPEs that would otherwise remain hidden. We conclude that the xWEI could be a valuable instrument in both disaster risk management and research.
Angelica Tarpanelli, Alessandro C. Mondini, and Stefania Camici
Nat. Hazards Earth Syst. Sci., 22, 2473–2489, https://doi.org/10.5194/nhess-22-2473-2022, https://doi.org/10.5194/nhess-22-2473-2022, 2022
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We analysed 10 years of river discharge data from almost 2000 sites in Europe, and we extracted flood events, as proxies of flood inundations, based on the overpasses of Sentinel-1 and Sentinel-2 satellites to derive the percentage of potential inundation events that they were able to observe. Results show that on average 58 % of flood events are potentially observable by Sentinel-1 and only 28 % by Sentinel-2 due to the obstacle of cloud coverage.
David P. Callaghan and Michael G. Hughes
Nat. Hazards Earth Syst. Sci., 22, 2459–2472, https://doi.org/10.5194/nhess-22-2459-2022, https://doi.org/10.5194/nhess-22-2459-2022, 2022
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A new method was developed to estimate changes in flood hazard under climate change. We use climate projections covering New South Wales, Australia, with two emission paths of business as usual and one with reduced emissions. We apply our method to the lower floodplain of the Gwydir Valley with changes in flood hazard provided over the next 90 years compared with the previous 50 years. We find that changes in flood hazard decrease over time within the Gwydir Valley floodplain.
Joseph T. D. Lucey and Timu W. Gallien
Nat. Hazards Earth Syst. Sci., 22, 2145–2167, https://doi.org/10.5194/nhess-22-2145-2022, https://doi.org/10.5194/nhess-22-2145-2022, 2022
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Coastal flooding can result from multiple flood drivers (e.g., tides, waves, river flows, rainfall) occurring at the same time. This study characterizes flooding events caused by high marine water levels and rain. Results show that wet-season coinciding sampling may better describe extreme flooding events in a dry, tidally dominated region. A joint-probability-based function is then used to estimate sea wall impacts on urban coastal flooding.
Erik Tijdeman, Veit Blauhut, Michael Stoelzle, Lucas Menzel, and Kerstin Stahl
Nat. Hazards Earth Syst. Sci., 22, 2099–2116, https://doi.org/10.5194/nhess-22-2099-2022, https://doi.org/10.5194/nhess-22-2099-2022, 2022
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We identified different drought types with typical hazard and impact characteristics. The summer drought type with compounding heat was most impactful. Regional drought propagation of this drought type exhibited typical characteristics that can guide drought management. However, we also found a large spatial variability that caused distinct differences among propagating drought signals. Accordingly, local multivariate drought information was needed to explain the full range of drought impacts.
Michael Dietze, Rainer Bell, Ugur Ozturk, Kristen L. Cook, Christoff Andermann, Alexander R. Beer, Bodo Damm, Ana Lucia, Felix S. Fauer, Katrin M. Nissen, Tobias Sieg, and Annegret H. Thieken
Nat. Hazards Earth Syst. Sci., 22, 1845–1856, https://doi.org/10.5194/nhess-22-1845-2022, https://doi.org/10.5194/nhess-22-1845-2022, 2022
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The flood that hit Europe in July 2021, specifically the Eifel, Germany, was more than a lot of fast-flowing water. The heavy rain that fell during the 3 d before also caused the slope to fail, recruited tree trunks that clogged bridges, and routed debris across the landscape. Especially in the upper parts of the catchments the flood was able to gain momentum. Here, we discuss how different landscape elements interacted and highlight the challenges of holistic future flood anticipation.
Marjolein J. P. Mens, Gigi van Rhee, Femke Schasfoort, and Neeltje Kielen
Nat. Hazards Earth Syst. Sci., 22, 1763–1776, https://doi.org/10.5194/nhess-22-1763-2022, https://doi.org/10.5194/nhess-22-1763-2022, 2022
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Many countries have to prepare for droughts by proposing policy actions to increase water supply, reduce water demand, or limit the societal impact. Societal cost–benefit analysis is required to support decision-making for a range of future scenarios, accounting for climate change and socio-economic developments. This paper presents a framework to assess drought policy actions based on quantification of drought risk and exemplifies it for the Netherlands’ drought risk management strategy.
Anna Rita Scorzini, Benjamin Dewals, Daniela Rodriguez Castro, Pierre Archambeau, and Daniela Molinari
Nat. Hazards Earth Syst. Sci., 22, 1743–1761, https://doi.org/10.5194/nhess-22-1743-2022, https://doi.org/10.5194/nhess-22-1743-2022, 2022
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This study presents a replicable procedure for the adaptation of synthetic, multi-variable flood damage models among countries that may have different hazard and vulnerability features. The procedure is exemplified here for the case of adaptation to the Belgian context of a flood damage model, INSYDE, for the residential sector, originally developed for Italy. The study describes necessary changes in model assumptions and input parameters to properly represent the new context of implementation.
Cited articles
Alfieri, L., Salamon, P., Pappenberger, F., Wetterhall, F., and Thielen, J.: Operational early warning systems for water-related hazards in Europe, Environ. Sci. Policy, 21, 35–49, https://doi.org/10.1016/j.envsci.2012.01.008, 2012. a
Alfieri, L., Salamon, P., Bianchi, A., Neal, J., Bates, P., and Feyen, L.: Advances in pan-European flood hazard mapping, Hydrol. Process., 28, 4067–4077, https://doi.org/10.1002/hyp.9947, 2014. a, b
Arabameri, A., Rezaei, K., Cerdá, A., Conoscenti, C., and Kalantari, Z.: A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran, Sci. Total Environ., 660, 443–458, https://doi.org/10.1016/j.scitotenv.2019.01.021, 2019. a, b, c, d, e, f, g
Bartholmes, J. C., Thielen, J., Ramos, M. H., and Gentilini, S.: The european flood alert system EFAS – Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts, Hydrol. Earth Syst. Sci., 13, 141–153, https://doi.org/10.5194/hess-13-141-2009, 2009. a
Bellos, V. and Tsakiris, G.: A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques, J. Hydrol., 540, 331–339, https://doi.org/10.1016/j.jhydrol.2016.06.040, 2016. a
Breiman, L., Friedman, J. H., Stone, C. J., and Olshen, R. A.: Classification and regression trees, 1st edn., Routledge, New York, 368 pp., https://doi.org/10.1201/9781315139470, 1984. a, b
Brunetti, M., Maugeri, M., Nanni, T., and Navarra, A.: Droughts and extreme events in regional daily Italian precipitation series, Int. J. Climatol., 22, 543–558, https://doi.org/10.1002/joc.751, 2002. a
Costabile, P., Costanzo, C., and Macchione, F.: Comparative analysis of overland flow models using finite volume schemes, J. Hydroinform., 14, 122–135, https://doi.org/10.2166/hydro.2011.077, 2012. a
Costache, R., Pham, Q. B., Avand, M., Thuy Linh, N. T., Vojtek, M., Vojteková, J., Lee, S., Khoi, D. N., Thao Nhi, P. T., and Dung, T. D.: Novel hybrid models between bivariate statistics, artificial neural networks and boosting algorithms for flood susceptibility assessment, J. Environ. Manage., 265, 110485, https://doi.org/10.1016/j.jenvman.2020.110485, 2020. a, b, c, d, e, f, g
De Risi, R., Jalayer, F., De Paola, F., and Lindley, S.: Delineation of flooding risk hotspots based on digital elevation model, calculated and historical flooding extents: the case of Ouagadougou, Stoch. Env. Res. Risk A., 32, 1545–1559, https://doi.org/10.1007/s00477-017-1450-8, 2018. a, b
Degiorgis, M., Gnecco, G., Gorni, S., Roth, G., Sanguineti, M., and Taramasso, A. C.: Classifiers for the detection of flood-prone areas using remote sensed elevation data, J. Hydrol., 470–471, 302–315, https://doi.org/10.1016/j.jhydrol.2012.09.006, 2012. a, b
Di Baldassarre, G., Kooy, M., Kemerink, J. S., and Brandimarte, L.: Towards understanding the dynamic behaviour of floodplains as human-water systems, Hydrol. Earth Syst. Sci., 17, 3235–3244, https://doi.org/10.5194/hess-17-3235-2013, 2013. a
Dodov, B. A. and Foufoula-Georgiou, E.: Floodplain Morphometry Extraction From a High-Resolution Digital Elevation Model: A Simple Algorithm for Regional Analysis Studies, IEEE Geosci. Remote Sens. Lett., 3, 410–413, https://doi.org/10.1109/LGRS.2006.874161, 2006. a, b
Domeneghetti, A., Carisi, F., Castellarin, A., and Brath, A.: Evolution of flood risk over large areas: Quantitative assessment for the Po river, J. Hydrol., 527, 809–823, https://doi.org/10.1016/j.jhydrol.2015.05.043, 2015. a
Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F. A., and Feyen, L.: Development and evaluation of a framework for global flood hazard mapping, Adv. Water Resour., 94, 87–102, https://doi.org/10.1016/j.advwatres.2016.05.002, 2016. a, b, c
Dottori, F., Alfieri, L., Bianchi, A., Skoien, J., and Salamon, P.: A new dataset of river flood hazard maps for Europe and the Mediterranean Basin region, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2020-313, in review, 2021. a
European Commission: River Flood Hazard Maps at European and Global Scale, Joint Research Centre Data Catalogue [data set], https://data.jrc.ec.europa.eu/collection/id-0054, last access: 7 April 2022. a
Everitt, B.: The Cambridge dictionary of statistics, 2nd edn., Cambridge University Press, Cambridge, United Kingdom, 2002. a
Faridani, F., Bakhtiari, S., Faridhosseini, A., Gibson, M. J., Farmani, R., and Lasaponara, R.: Estimating Flood Characteristics Using Geomorphologic Flood Index with Regards to Rainfall Intensity-Duration-Frequency-Area Curves and CADDIES-2D Model in Three Iranian Basins, Sustainability 12, 7371, https://doi.org/10.3390/su12187371, 2020.
Gnecco, G., Morisi, R., Roth, G., Sanguineti, M., and Taramasso, A. C.: Supervised and semi-supervised classifiers for the detection of flood-prone areas, Soft Comput., 21, 3673–3685, https://doi.org/10.1007/s00500-015-1983-z, 2017. a, b
GRASS Development Team: Geographic Resources Analysis Support System (GRASS) Software, Version 7.6, Open Source Geospatial Foundation, https://grass.osgeo.org (last access: 31 March 2022), 2019. a
Guha-Sapir, D., Hoyois, P., Wallemacq, P., and Below, R.: Annual Disaster Statistical Review 2016: The Numbers and Trends, CRED, Brussels, Belgium, 2016. a
Hastie, T., Tibshirani, R., and Friedman, J.: The Elements of Statistical Learning, Springer Series in Statistics, Springer New York, New York, NY, https://doi.org/10.1007/978-0-387-84858-7, 2009. a, b, c, d
Ho, W., Xu, X., and Dey, P. K.: Multi-criteria decision making approaches for supplier evaluation and selection: A literature review, Eur. J. Oper. Res., 202, 16–24, https://doi.org/10.1016/j.ejor.2009.05.009, 2010. a
Horritt, M. S. and Bates, P. D.: Evaluation of 1D and 2D numerical models for predicting river flood inundation, J. Hydrol., 268, 87–99, https://doi.org/10.1016/S0022-1694(02)00121-X, 2002. a
Hosseiny, H., Nazari, F., Smith, V., and Nataraj, C.: A Framework for Modeling Flood Depth Using a Hybrid of Hydraulics and Machine Learning, Sci. Rep., 10, 8222, https://doi.org/10.1038/s41598-020-65232-5, 2020.
ISPRA: Mosaicature Nazionali ISPRA pericolosità frane-alluvioni, Network of the National Environmental Information System (SINAnet) [data set], http://www.sinanet.isprambiente.it/it/sia-ispra/download-mais/mosaicature-nazionali-ispra-pericolosita-frane-alluvioni, last access: 7 April 2022. a
Janizadeh, S., Avand, M., Jaafari, A., Phong, T. V., Bayat, M., Ahmadisharaf, E., Prakash, I., Pham, B. T., and Lee, S.: Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran, Sustainability, 11, 5426, https://doi.org/10.3390/su11195426, 2019. a, b, c, d, e, f
Jongman, B., Koks, E. E., Husby, T. G., and Ward, P. J.: Increasing flood exposure in the Netherlands: implications for risk financing, Nat. Hazards Earth Syst. Sci., 14, 1245–1255, https://doi.org/10.5194/nhess-14-1245-2014, 2014. a
Kirkby, M. J.: Hydrograph modelling strategies, in: Processes in physical and human geography, Heinemann, Oxford, 69–90, 1975. a
Khosravi, K., Pham, B. T., Chapi, K., Shirzadi, A., Shahabi, H., Revhaug, I., Prakash, I., and Tien Bui, D.: A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran, Sci. Total Environ., 627, 744–755, https://doi.org/10.1016/j.scitotenv.2018.01.266, 2018. a, b, c, d, e, f, g
Manfreda, S., Sole, A., and Fiorentino, M.: Can the basin morphology alone provide an insight into floodplain delineation?, in: Flood Recovery, Innovation and Response I, edited by: Proverbs, D., Brebbia, C. A., and Penning-Roswell, E., WITpress, London, England, 47–56, https://doi.org/10.2495/FRIAR080051, 2008. a, b
Manfreda, S., Di Leo, M., and Sole, A.: Detection of Flood-Prone Areas Using Digital Elevation Models, J. Hydrol. Eng., 16, 781–790, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000367, 2011. a, b
Manfreda, S., Nardi, F., Samela, C., Grimaldi, S., Taramasso, A. C., Roth, G., and Sole, A.: Investigation on the use of geomorphic approaches for the delineation of flood prone areas, J. Hydrol., 517, 863–876, https://doi.org/10.1016/j.jhydrol.2014.06.009, 2014. a, b
Manfreda, S., Samela, C., Gioia, A., Consoli, G. G., Iacobellis, V., Giuzio, L., Cantisani, A., and Sole, A.: Flood-prone areas assessment using linear binary classifiers based on flood maps obtained from 1D and 2D hydraulic models, Nat. Hazards, 79, 735–754, https://doi.org/10.1007/s11069-015-1869-5, 2015. a, b, c, d, e
Manfreda, S. and Samela, C.: A digital elevation model based method for a rapid estimation of flood inundation depth, J. Flood Risk Manag., 12, e12541, https://doi.org/10.1111/jfr3.12541, 2019. a
Mosavi, A., Ozturk, P., and Chau, K.: Flood Prediction Using Machine Learning Models: Literature Review, Water, 10, 1536, https://doi.org/10.3390/w10111536, 2018. a, b
Nardi, F., Vivoni, E. R., and Grimaldi, S.: Investigating a floodplain scaling relation using a hydrogeomorphic delineation method: Hydrogeomorphic Floodplain Delineation Method, Water Resour. Res., 42, 105–114, https://doi.org/10.1029/2005WR004155, 2006. a, b, c
Noman, N. S., Nelson, E. J., and Zundel, A. K.: Review of Automated Floodplain Delineation from Digital Terrain Models, J. Water Resour. Plan. Manag., 127, 394–402, https://doi.org/10.1061/(ASCE)0733-9496(2001)127:6(394), 2001. a
OpenStreetMap contributors: Planet dump retrieved from https://planet.osm.org, https://www.openstreetmap.org (last access: 31 March 2022), 2017. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, É.: Scikit-learn: Machine Learning in Python, arXiv [preprint], J. Mach. Learn. Res., 12, arxiv:1201.0490, 2011. a, b
Persiano, S., Ferri, E., Antolini, G., Domeneghetti, A., Pavan, V., and Castellarin, A.: Changes in seasonality and magnitude of sub-daily rainfall extremes in Emilia-Romagna (Italy) and potential influence on regional rainfall frequency estimation, J. Hydrol. Reg. Stud., 32, 100751, https://doi.org/10.1016/j.ejrh.2020.100751, 2020. a
QGIS Development Team: QGIS Geographic Information System, QGIS Association, https://www.qgis.org (last access: 31 March 2022), 2021. a
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M. G., Tomasella, J., and Waterloo, M. J.: HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia, Remote Sens. Environ., 112, 3469–3481, https://doi.org/10.1016/j.rse.2008.03.018, 2008. a
Requena, A. I., Prosdocimi, I., Kjeldsen, T. R., and Mediero, L.: A bivariate trend analysis to investigate the effect of increasing urbanisation on flood characteristics, Hydrol. Res., 48, 802–821, https://doi.org/10.2166/nh.2016.105, 2017. a
Samela, C., Albano, R., Sole, A., and Manfreda, S.: A GIS tool for cost-effective delineation of flood-prone areas, Comput. Environ. Urban Syst., 70, 43–52, https://doi.org/10.1016/j.compenvurbsys.2018.01.013, 2018. a
Tarboton, D. G., Bras, R. L., and Rodriguez-Iturbe, I.: On the extraction of channel networks from digital elevation data, Hydrol. Process., 5, 81–100, https://doi.org/10.1002/hyp.3360050107, 1991. a
Tarboton, D. G.: Terrain Analysis Using Digital Elevation Models in Hydrology, 23rd ESRI International Users Conference, San Diego, California, 6–9 July 2003. a
Tavares da Costa, R., Manfreda, S., Luzzi, V., Samela, C., Mazzoli, P., Castellarin, A., and Bagli, S.: A web application for hydrogeomorphic flood hazard mapping, Environ. Model. Softw., 118, 172–186, https://doi.org/10.1016/j.envsoft.2019.04.010, 2019.
a, b, c, d
Tavares da Costa, R., Zanardo, S., Bagli, S., Hilberts, A. G. J., Manfreda, S., Samela, C., and Castellarin, A.: Predictive Modeling of Envelope Flood Extents Using Geomorphic and Climatic‐Hydrologic Catchment Characteristics, Water Resour. Res., 56, e2019WR026453, https://doi.org/10.1029/2019WR026453, 2020. a
Triantaphyllou, E.: Multi-Criteria Decision Making Methods, in: Multi-Criteria Decision Making Methods: A Comparative Study, Appl. Optimizat., Springer US, Boston, MA, 5–21, https://doi.org/10.1007/978-1-4757-3157-6, 2000. a
Uboldi, F. and Lussana, C.: Evidence of non-stationarity in a local climatology of rainfall extremes in northern Italy: Non-Stationarity in a local climatology of rainfall extremes, Int. J. Climatol., 38, 506–516, https://doi.org/10.1002/joc.5183, 2018. a
Wang, Z., Lai, C., Chen, X., Yang, B., Zhao, S., and Bai, X.: Flood hazard risk assessment model based on random forest, J.
Hydrol., 527, 1130–1141, https://doi.org/10.1016/j.jhydrol.2015.06.008, 2015. a, b, c
Williams, W. A., Jensen, M. E., Winne, J. C., and Redmond, R. L.: An Automated Technique for Delineating and Characterizing Valley-Bottom Settings, in: Monitoring Ecological Condition in the Western United States, edited by: Sandhu, S. S., Melzian, B. D., Long, E. R., Whitford, W. G., and Walton, B. T., Springer Netherlands, Dordrecht, 64, 105–114, https://doi.org/10.1007/978-94-011-4343-1_10, 2000. a
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F., Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high-accuracy map of global terrain elevations: Accurate Global Terrain Elevation map, Geophys. Res. Lett., 44, 5844–5853, https://doi.org/10.1002/2017GL072874, 2017. a, b, c, d, e
Yamazaki Lab: MERIT DEM: Multi-Error-Removed Improved-Terrain DEM, Institute of Industrial Sciences, The University of Tokyo [data set], https://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ (last access: 7 April 2022), 2018. a
Youden, W. J.: Index for rating diagnostic tests, Cancer, 3, 32–35, https://doi.org/10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3, 1950. a
Short summary
We retrieve descriptors of the terrain morphology from a digital elevation model of a 105 km2 study area and blend them through decision tree models to map flood susceptibility and expected water depth. We investigate this approach with particular attention to (a) the comparison with a selected single-descriptor approach, (b) the goodness of decision trees, and (c) the performance of these models when applied to data-scarce regions. We find promising pathways for future research.
We retrieve descriptors of the terrain morphology from a digital elevation model of a 105 km2...
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